Similarity Analysis and Modeling in Mobile Societies: The Missing Link
Gautam Thakur, Ahmed Helmy, Wei-Jen Hsu

TL;DR
This paper introduces a behavioral-profile based method to analyze and model user similarity in mobile societies, revealing the limitations of current mobility models and emphasizing the need for models that explicitly incorporate user behavioral diversity.
Contribution
It proposes a novel similarity measure based on user location preferences and demonstrates the inadequacy of existing mobility models in capturing behavioral diversity.
Findings
Real mobile societies exhibit diverse behavioral clusters.
Existing models produce homogeneous user populations.
Behavioral similarity is crucial for future mobility modeling.
Abstract
A new generation of "behavior-aware" delay tolerant networks is emerging in what may define future mobile social networks. With the introduction of novel behavior-aware protocols, services and architectures, there is a pressing need to understand and realistically model mobile users behavioral characteristics, their similarity and clustering. Such models are essential for the analysis, performance evaluation, and simulation of future DTNs. This paper addresses issues related to mobile user similarity, its definition, analysis and modeling. To define similarity, we adopt a behavioral-profile based on users location preferences using their on-line association matrix and its SVD, then calculate the behavioral distance to capture user similarity. This measures the difference of the major spatio-temporal behavioral trends and can be used to cluster users into similarity groups or…
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Taxonomy
TopicsOpportunistic and Delay-Tolerant Networks · Human Mobility and Location-Based Analysis · Caching and Content Delivery
